#merge the data
dat1 = read.csv('https://raw.githubusercontent.com/jhu-advdatasci/2018/master/data/KFF/healthcare-spending.csv',skip=2)[1:52,]
dat2 = read.table('https://raw.githubusercontent.com/bcaffo/ds4bme/master/data/federalRegions.txt',skip = 1, sep ='\t')
colnames(dat2) = c('Region','Location')
dat  = left_join(dat1,dat2,by = 'Location')
#Exclude some regions
colnames(dat)[c(-1,-26)] =c(1991:2014)
dat = mutate(dat,avgSpending = apply(dat[c(-1,-26)], 1, mean))
rownames(dat) = dat[,1]
dat = dat[!rownames(dat) %in% c('United States','District of Columbia'),]

#plot
# ggplot(dat, aes(Region,y = avgSpending,fill = Location)) + geom_col()

plot_ly(dat,x =~Region, y = ~avgSpending, color= ~Location, type = 'bar')%>%
  layout(yaxis = list(title = 'Average Spending'), barmode = 'stack')